Expectations on chatbots are as big as linked disillusions

Really strong expectations are hiding behind the chatbots trend. Customers are willing to have :

Open services when they need them and not when they need them and not when the company is open

Get simple answers to simple problems

Have a relevant support : more autonomy when possible but also tailored answers (which can be easier to provide than personalized answers by the way)

Something easy to use, whatever the solution. If mobile applications are rejected, being intrusive and hard to use, this does not mean at all a chatbot adoption. This is a paradox. Taking France as an example, most of the population is not "digital fluenté. Some new terms have even been invented to describe this new kind of handicap. In an hyper-connected world, "dysnumerism" is getting wider. We think only retired people are concerned. Unfortunately, this is a mistake, and all the clusters of population are being concerned : 13 million french people having difficulty with digital (sociéténumérique.gouv.fr).

Thus, there is a real need to provide systems which would be more accessible and intuitive, not to say "user friendly".

How to efficiently invest in Customer eXperience enhancement?

1 - "HEAT" your processes

Doing the same thing with a different technology does not bring any value. Replacing an IVR (Interactive Voice Response software) with limited Natural Language Recognition can even lead to worse client interaction (this is a real life example of replacing typing client number on a keyboard with dictating it... without success...) . In the same way, static web or application content replacement with a chatbot will not bring higher adoption from customers. You need to globally redesign your users journeys :

Human : Put individuals back in the middle of... everything : systems, interactions, concerns... Consider not only customers but all end-users, including business professionals which role shall get more and more important.

Exceptional: Look for the items which will make your service more relevant to your customer; which will make it better adopted by them; and which will enhance User eXperience compared to your competitors, or compared to your existing processes.

Architecture : Service value relies on service data and business functions. We can't think isolated front-end only. It is essential to consider the overall architecture of the enterprise and its ecosystem. A unique solution to an issue is a wrong way sign. One shall combine services and technological options (e.g. put in place search engines coupled with NLP and chatbots...)

Tailored : Start thinking again about what is useful to the user, depending on his interaction points (action, life key event...). And continue focusing of course on usability.

2 - Redesign interactions

Adding an additional layer of Natural Language Processing (NLP) is a first step towards a more efficient interaction. However, you should not try to mimic human agents with chatbots. Indeed, MIT prove (cf. this study in 2018) that the more complex the conversation agent, the greater discomfort.

Chatbots engine are becoming commodity software. It might be time to switch to an even more natural interface. Conversational interfaces (Amazon echo, Google home...) are ramping-up.

3 - Get knowledgeable on the topic

Nowadays, everybody pretends to "do AI" (mixing in a wonderful salad bowl concepts like Machine Learning, Neural networks, decision trees...). A huge bunch of startups have run into it.

Sample ecosystem from Capgemini AI startups quadrant 2019

Most of the companies launched prototypes. They now face major issues :

Take on technology: Knowledge transfer can be tricky. This is one more impediment to go beyond just a nice to have feature..

Take on concepts: It is worth saying it again and again, there is no such thing as unique "AI". As a consequence, a chatbot project is not a way to tick the "AI" box of an IT strategic plan (and even less if we consider business matters...). There a re a lot of "AIs" and key questions to do a good selection are around knowledge to be shared better than technology (http://food4thought.fr/en/ai-cognition-loop/).

How did everything go wrong?

The promise of enhanced User eXperience is not held

Most of the time, you must be an IT professional or at least nerd to be able to use a chatbot. You must be "machine language fluent" and know which key words to use. You also have to guess what the chatbot is able to do within a given web page or context. Just take the example of this french subway route calculator, which is certainly able to do a lot of things, except route calculation!

Example : RATP route calculation. Please close this damned pop-up, I just wanna go from point A to point B!

Many of them did not have the right target

It's easier to use a "coded language" for use cases internal to the enterprise, knowledge exchange between business experts and field agents for example. in this case, chatbots can bring additional value when combined, for example, with search engine technologies. Unfortunately, many marketing entities decided to become owners of the topic. As a consequence, customers started to reject them. On the other hand, "internal" chatbots had a modest success.

Customer relationship is still considered as a center of costs

Just like many innovation projects, calculating or anticipating potential return on investment is quite hard. multiple drivers impact customer satisfaction. As an example, sales increase can of course result from efficient marketing campaigns... On the contrary support centers cost reduction is fully predictable and measurable. It is thus not a surprise that CxOs priority was put on automation of low value tasks instead of real customer valued interfaces.

From the services and products providers point of view: "I'm late, everybody already have chatbots!"

Many Points of Views (not even having real quantitative and qualitative studies) tell us that most of enterprises and business entities now want to put in place chatbots.

This example, 10 key figures about chatbot market explains us that 80% of companies will use chatbots in their customer interactions in 2020 (quoting a 2016 Business Insider report, which sources I'm still looking for).

Everybody does it, it must be a good idea...

From the end-user point of view: « Everybody uses chatbots. I'm surely the only one to know nothing to digital!"

"You can find it on the internet, so it must be true : everybody loves chatbots". What is your personal feeling about it? You might have been lucky and use one which was "not so bad", replacing a static FAQ. But in most cases, it is only one more popup on your screen. And I'm sure you will have tested how it coped with insults (everybody did that once... feel free, you're not the only one...).

Few people are in fact satisfied with dealing with a chatbot. It is now to the internet what IVR was to phone. Primary purpose is not to enhance User eXperience, but to reduce operations costs, even if this precisely means making this experience worse! Lets notice this study by the way "yes chatbots are incredibly efficient but your customers hate them", « 90% of surveyed companies acknowledge that creating a better customer experience is not one of their priorities".

These projects were however somehow useful…

We're coming to an edge. One more time CxOs (mainly CIOs and CMOs) start to notice that technology is not an end. Given implementation difficulties, mandatory user experience requirements are raised; Useless FAQs are clarified; Real users questions are measured to better identify expectations; AI replacing humans illusion is fading (Customers annoyed by Artificial Stupidity) to think again how to put back human at the heart of processes and interactions.

Let's now switch from "Proof of Concepts" to real "Minimum Viable Products", and not like one more marketing buzzword.